FUSE: Improving the estimation and imputation of variant impacts in functional screening.

Autor:	Yu T; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA., Fife JD; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA., Bhat V; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA., Adzhubey I; Department of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA., Sherwood R; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: rsherwood@bwh.harvard.edu., Cassa CA; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: ccassa@bwh.harvard.edu.
Jazyk:	angličtina
Zdroj:	Cell genomics [Cell Genom] 2024 Oct 09; Vol. 4 (10), pp. 100667.
DOI:	10.1016/j.xgen.2024.100667
Abstrakt:	Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening. Competing Interests: Declaration of interests The authors declare no competing interests. (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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